Note: Descriptions are shown in the official language in which they were submitted.
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GENERATING METRICS BASED ON CLIENT DEVICE OWNERSHIP
BACKGROUND
[0001] This invention generally relates to generating metrics, and more
specifically to
generating metrics based on client device ownership.
[0002] Advertisers expend significant resources on advertisements promoting
their
products or services. Often, advertisers communicate advertisements to
potential customers
using various forms of media including television, newspapers, radio, cinema,
billboards, the
Internet and/or the like. In recent years, the online distribution of
advertisements (e.g.,
distribution via the Internet) has become increasingly popular among
advertisers.
[0003] Advertisers are frequently interested in measuring the effectiveness
of their
advertisements on different groups of people. For example, an advertiser may
be interested in
measuring the effectiveness of its advertisements presented to owners of
various client
devices. To generate metrics describing the effectiveness of advertising,
associations
between exposure to advertisements and ownership of the client devices are
needed.
Determining device ownership and advertisement associations is generally a
manual process
that is often subject to reporting inaccuracies. Accordingly, conventionally
generating
advertising metrics based on client device ownership is a laborious task
producing imprecise
results.
SUMMARY
[0004] Embodiments of the invention are directed to generating metrics for
one or more
advertisements based on ownership of client devices. To generate the metrics,
a social
networking system automatically identifies users of the social networking
system as owners
of various client devices (e.g., mobile phones, tablet devices, etc.). In one
implementation,
the social networking system identifies a user as an owner of a client device
if the user's
account on the social networking system has been accessed by a native software
application
or by a web browsing application installed on the client device. In one
embodiment, to more
accurately identify owners, the social networking system identifies a user as
an owner of a
client device after the user's account is accessed by the native software
application or by the
web browsing application at least a threshold number of times or at least a
threshold
percentage of times. In other embodiments, the social networking system also
analyzes social
signals from data maintained by the social networking system to identify
whether a user is an
owner of a client device. For example, ownership may be determined based on
information
in the user profiles or other content of a user's friends over the social
networking system.
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Illustratively, a comment posted by a user's friend to the social networking
system may
congratulate the user for purchasing a particular mobile phone model.
[0005] After identifying owners of various client devices, the social
networking system
identifies one or more exposures of the identified owners to one or more
advertisements. The
social networking system also obtains additional information associated with
the owners of
the various client devices. Examples of the additional information include
purchase
transaction information, observed online dnd offline user actions, polling
data, or any other
information suitable for generating advertising metrics.
[0006] Based on the advertisement exposures and/or the obtained additional
information,
the social networking system generates various metrics for the one or more
advertisements
with respect to the identified owners. In one aspect, the generated metrics
may be broken
down according to types for the various client devices. For example, the
generated metrics
may be segmented based on client device model, product number, operating
system,
manufacturer, etc. As an example, different metrics may be generated for the
owners of the
APPLE IPHONE 4, the APPLE IPAD , and the Amazon KINDLE FIRE .
[0007] In one embodiment, metrics generated by the social networking system
may
describe numbers or percentages of exposures for the one or more
advertisements with
respect to the owners of various types of client devices. For example, an
"exposure" metric
may indicate that 2,000 APPLE IPHONE 5 owners have viewed a particular
advertisement while 300 owners of the NOKIA LUMIA 900 have viewed the same
advertisement. In another embodiment, generated metrics may measures the
effectiveness of
the one or more advertisements on owners of the various types of client
devices. For
example, an advertisement may promote a particular automobile model. A
"conversion"
metric may indicate the effectiveness of the advertisement on the owners of
the APPLE
IPHONE 5 in facilitating the owners to perform searches for information about
the
automobile model.
[0008] In one embodiment, metrics generated by the social networking system
may
describe the effectiveness of the one or more advertisements in promoting
ownership of
particular types of client devices. More specifically, the social networking
system generates
conversion metrics measuring the effect of the advertisements in driving the
subsequent
purchase and/or ownership of a particular type of client device. For example,
a metric may
describe the effectiveness of an advertisement promoting the SAMSUNG GALAXY
TAB 2
in encouraging ownership of the SAMSUNG GALAXY TAB 2. To generate the metric,
the social networking system may identify users accessing their account from a
SAMSUNG
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GALAXY TAB 2 after being presented with an advertisement for the SAMSUNG
GALAXY TAB 2.
[0009] In one embodiment, the metrics generated by the social networking
system may
provide information regarding insights into market share or ownership shifts.
To generate
such metrics, the social networking system may identify client devices
previously owned by
users. The social networking system may additionally identify client devices
currently owned
,
by the same users. Based on comparisons of the identified information, the
social network
system may generate metrics indicating shifts or changes related to the
ownership of the client
devices.
[0010] Identifying owners of client devices and generating metrics based on
the identified
device ownership in the manner described enable advertising metrics relating
to client device
ownership to be efficiently and accurately generated. Hence, advertisers can
obtain a better
understanding of the effectiveness of their advertisements as related to
client device
ownership. This allows advertisers to better tailor their advertisements to
meet various
advertising objectives.
[0011] The features and advantages described in this summary and the
following detailed
description are not all-inclusive. Many additional features and advantages
will be apparent to
one of ordinary skill in the art in view of the drawings, specification, and
claims hereof.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] FIG. 1 is a high level block diagram illustrating a system
environment suitable for
operation of a social networking system, in accordance with an embodiment of
the invention.
[0013] FIG. 2 is a block diagram of various components of a social
networking system, in
accordance with an embodiment of the invention.
[0014] FIG. 3 is a flow chart of a process for generating advertising
metrics according to
client device ownership, in accordance with an embodiment of the invention.
[0015] FIG. 4 is a flow chart of a process for generating advertising
metrics measuring
advertising impact on client device ownership, in accordance with an
embodiment of the
invention.
[0016] The Figures depict various embodiments of the present invention for
purposes of
illustration only. One skilled in the art will readily recognize from the
following discussion
that alternative embodiments of the structures and methods illustrated herein
may be
employed without departing from the principles of the invention described
herein.
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DETAILED DESCRIPTION
System Architecture
[0017] FIG. 1 is a high level block diagram illustrating a system
environment 101 suitable
for operation of a social networking system 100. In one aspect, the system
environment 101
enables the automatic generation of advertising metrics based on client device
ownership. As
shown in FIG. 1, the system environment includes one or more client devices
102, one or
more third-party websites 103, a social networking system 100, and a network
104. While
FIG. 1 shows three client devices 102 and one third-party website 103, it
should be
appreciated that any number of these entities (including millions) can be
included. In
alternative configurations, different entities can also be included in the
system environment
101.
[0018] The client devices 102 are one or more computing devices that
receive user input,
as well as transmit and receive data via the network 104 to the social
networking system 100.
Some of the client devices 102 include an installed native software
application for accessing
the social networking system 100. The native software application may be a
software
application configured to be executed within a computing environment specific
to a client
device 102. For example, the native software application is configured to be
executed by an
operating system executed by the client device 102. In some embodiments, the
client device
102 includes various native software applications for accessing different
entities, such as
various third-party websites 103 and/or the social networking system 100.
[0019] One or more of the client devices 102 may include a web browsing
application,
such as APPLE SAFARI , MICROSOFT INTERNET EXPLORER , GOOGLE
Chrome, Mozilla FIREFOX , etc. The web browsing application allows the client
device
102 to exchange information with one or more third-party websites 103 and/or
with the social
networking system 100 via the network 104. The web browsing application
included on a
client device 102 may depend on one or more attributes of the client device
102, such as an
operating system used by the client device 102, or any other suitable
attribute of the client
device 102.
[0020] Each of the client devices 102 provides identifying information
associated with a
user when accessing the social networking system 100. The identifying
information is used
by the social networking system 100 to identify a user account associated with
the user of a
client device 102. Examples of identifying information include a username, a
password, a
login credential, or other information suitable for identifying a user account
stored by the
social networking system 100. Further, a client device 102 may provide
information
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describing one or more attributes of the client device 102 when communicating
with the
social networking system 100. For example, the attribute information sent to
the social
networking system 100 includes data describing a model of the client device
102, a part
number associated with the client device 102, a manufacturer associated with
the client
device 102, an operating system associated with the client device 102, a
native application
used by the client device 102 to access the social networking system 100, or
any other
suitable information. As further described below, the social networking system
100 uses one
or more of the attributes of the client device 102 to generate one or more
metrics for
advertisements.
[0021] Examples of client devices 102 include desktop computers, laptop
computers,
tablet computers (pads), mobile phones, personal digital assistants (PDAs),
gaming devices,
appliances (e.g., refrigerators), vehicles (e.g., automobiles, boats,
airplanes), or any other
devices including computing functionality and data communication capabilities.
The client
devices 102 are configured to communicate via the network 104, which may be
any
combination of local area and/or wide area networks using both wired and
wireless
communication systems. For example, the network 104 may be any combination of
the
Internet, a mobile network, a local area network (LAN), a wired or wireless
network, a private
network, a virtual private network and/or any other suitable communication
mechanisms.
The third-party website 103 is coupled to the network 104 to communicate with
the social
networking system 100 and/or with one or more client devices 102.
[0022] The social networking system100'is a computing system allowing its
users to
communicate or otherwise interact with each other and access content as
described herein. In
one embodiment, the social networking system 100 stores user accounts for one
or more
social networking system users. Associated with the user accounts, the social
networking
system 100 stores user profiles describing the social networking system users,
including
biographic, demographic, and other types of descriptive information, such as
work
experience, educational history, hobbies or preferences, location, and the
like. Using
information in the user profiles, connections between user profiles, and
actions associated
with user profiles, the social networking system 100 maintains a social graph
describing
connections between various users. Each connection may define a particular
relationship
between two users, such as a friendship relationship, a fan relationship, a
follower
relationship, etc. The social networking system 100 additionally stores other
objects, such as
fan pages, events, groups, advertisements, general postings, etc.
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[0023] FIG. 2 is an example block diagram of various components of one
embodiment of
the social networking system 100. In alternative configurations, different
and/or additional
components may be included in the system 100.
[0024] The account store 215 stores information for user accounts of
various social
networking system users. The information for a user account may include user
identifiers, a
username, a user password, user settings (e.g.: user privacy settings),
identifiers of client
devices 102 associated with a user, or other similar information. Each user
account is
associated with a corresponding social network user profile. Data included in
the account
store 215 may be encrypted or otherwise secured to prevent unauthorized access
to the data.
[0025] The profile store 205 stores user profiles associated with social
networking system
users. Each user profile may include demographic and other information
associated with a
particular user. Examples of information associated with a user include: the
user's gender,
age, geographical location, education or professional affiliations, group
memberships,
interests, activities, income, nationality, race, and/or the like. For
example, a stored user
profile indicates that a particular user is 25 years old, lives in Cheyenne,
works as a doctor,
and enjoys horseback riding. In one embodiment, each user profile may also be
associated
with and/or include information about a user's connections (e.g., friends) in
the social
networking system 100 to other users of the social networking system 100. In
one
embodiment, data included in the profile store 205 may be encrypted or
otherwise secured to
prevent unauthorized access.
[0026] The activity data store 245 stores information describing one or
more activities of
users through the social networking system 100 and/or external to the social
networking
system 100. The information stored by the activity data store 245 describes
any suitable
online or offline activities. For example, the activity data store 245
includes data describing
uses of a client device 102 by a user to login to or otherwise access the
social networking
system 100.
[0027] Information included in the activity data store 245 may also
identify types of
actions performed by users. Example types of activities include: expressing a
preference for
an object (i.e., "liking" the object), expressing a desire for an object
(i.e., "wanting" the
object), commenting on an object, sharing an object, searching for an object,
viewing an
object, posting content, and generating content and/or advertisements. The
activity data store
245 further includes data describing actions performed with respect to the
users, such as
presentation of content to a user and/or exposure of one or more
advertisements to the user.
Additionally, the activity data store may store certain attributes of a client
device 102 used to
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perform an activity or otherwise associated with an activity (e.g., a model of
the client device
102, a part number associated with the client device 102, a manufacturer
associated with the
client device 102, an operating system associated with the client device 102,
a native
application used by the client device 102 to access the social networking
system 100, etc.).
[0028] In one embodiment, the activity data store 245 also stores polling
data and/or
information regarding purchases by social' netWorking system users. Location
data associated
with users may be stored in the activity data store 245. For example, the
activity data store
245 stores data identifying a geographic location and a time associated with
the geographic
location indicating a user is at the geographic location. The geographic
information may be
received via an explicit communication from the user (e.g., a "check-in"), via
communication
from a client device 102, or via any suitable action. To prevent unauthorized
access, data in
the activity data store 245 may be encrypted, or otherwise secured.
[0029] The advertising store 246 stores data describing one or more
advertisements and
presentation of one or more advertisements to social networking system users.
For example,
the advertising store 246 stores an advertisement, data identifying an
advertiser associated
with the advertisement and other parameters associated with the advertisement.
Additionally,
targeting criteria may be stored and associated with an advertisement.
Targeting criteria
identifies one or more characteristics of a user eligible to be presented an
associated
advertisement. For example, targeting criteria specifies attributes from a
user profile, such as
user demographics (e.g., gender, age, geographical region, stated interests or
preferences,
professional, personal, or educational affiliations, income or other data
included in a user
profile). Different types of user affiliations may be specified by targeting
criteria, such as
memberships in groups, lists, networks, forums, and clubs within the social
networking
system. For example, an advertisement may be targeted towards graduates from a
list of
specific colleges and universities.
[0030] Targeting criteria may also specify attributes of a user's actions
inside and/or
outside of the social networking system 100. Example targeting criteria based
on user actions
may specify frequency of use of the social networking system 100, length of
time logged-in to
the social networking system 100, access or use of specific features of the
social networking
system 100 or destinations outside the social networking system 100. For
example, an
advertisement may be targeted to users who have used the social networking
system 100 at
least five times per week for the past month, and who have used a gift giving
application
within the last three days. Hence, the targeting criteria may comprise any
data maintained by
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the social networking system 100 or any suitable combination of data
maintained by the
social networking system 100.
[0031] The web server 250 exchanges data between the social networking
system 100,
one or more of the client devices 102, and/or one or more third-party websites
130 via the
network 104. For example, the web server 250 includes a mail server or other
messaging
,
functionality for receiving and routing messages between the social networking
system 100
and the client devices 102 or third-party websites 103. The messages can be
instant
messages, queued messages (e.g., email), short message service (SMS) messages,
multimedia
messaging service (MMS) messages, or any other suitable type of message. In
one
embodiment, the web server 250 may receive a request for content to be
displayed to a user of
a client device 102, and the content is presented along with one or more
advertisements; the
content and/or advertisements are provided to the client device 102 via the
web server 250.
[0032] In one embodiment, the web server 250 serves one or more web pages
and/or
other content that are collectively referred to as a website of the social
networking system
100. The web server 250 allows users, via web browsing applications or native
applications
installed on the client devices 102, to access functionalities of the social
networking system
100. In various embodiments, the web server 250 may use one or more
application
programming interfaces (APIs) to allow native software applications installed
on the client
devices 102 to directly access the functionalities of the social networking
system 100.
[0033] Data received by the web server 250 from a client device 102
includes information
specifying certain attributes of the client device 102 (e.g., a model of the
client device 102, a
part number associated with the client device 102, a manufacturer associated
with the client
device 102, an operating system associated with the client device 102, a
native application
used by the client device 102 to access the social networking system 100,
etc.). Data received
from a client device 102 also includes information identifying a user account
associated with
a client device user, such as a username.
[0034] The data logger 260 identifies and stores information describing one
or more
activities performed through the social networking system 100 and/or external
to the social
networking system 100 in the activity data store 245. For example the data
logger 260 logs
information regarding an action performed by a user via the social networking
system 100 in
the activity data store 245. As another example, the data logger 260 logs
information
regarding presentation of an advertisement to a user via the social networking
system 100 in
the activity data store 245. In one embodiment, the data logger 260 logs
identification
information (e.g., a username) for the user associated with an action to the
activity data store
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245. Additional information, such as data describing a client device 102
associated with the
user or with the action (e.g., a device model identifier) may also be logged
by the data logger
260.
[0035] The metric generator 275 generates metrics for one or more
advertisements based
at least in part on client device ownership, To generate the metrics, the
metric generator 275
identifies users of the social networking system as owners of the client
devices 102. In one
aspect, the metric generator 275 identifies the owners based on accesses
performed to the
owners' user accounts over the social networking system by native software
applications
and/or web browsing applications installed on the client devices 102.
Identification may also
be based on one or more social signals. After identifying the owners of the
client devices
102, the metric generator 275 identifies one or more exposures of the owners
to one or more
advertisements. Based on the identified owners of the client devices 102 and
the identified
exposures to the advertisements, the metric generator 275 generates metrics
for the one or
more advertisements with respect to the identified owners. The metrics may be
categorized
based on different attributes of the client devices 102, such as by client
device model, part
number, etc.
Process for Generating Advertising Metrics According to Client Device
Ownership
[0036] FIG. 3 illustrates one embodiment of a process 300 for generating
advertising
metrics according to client device ownership. Other embodiments can perform
the steps of
the process 300 in different orders and can include different, additional,
and/or fewer steps.
[0037] The social networking system 100 identifies 310 users of the social
networking
system 100 owning one or more client devices 102. An owner of a particular
client device
102 may be a social networking system user that is the primary user of a
client device 102.
An owner may alternatively or additionally be a social networking system user
that is a
regular user of a client device 102, so multiple owners may be identified
based on usage of a
client device 102.
[0038] In one aspect, one or more ownership identification policies or
rules are used to
identify 310 a user as an owner of a client device 102. In one implementation,
the social
networking system 100 identifies a user as an owner based on communications
from a native
software application of the social networking system 100 installed on a client
device 102 used
by the user to access the social networking system 100. More specifically,
communications
from the native software application may include user identifying information
(e.g., a user id,
username, user password, etc.) for accessing the social networking system 100.
From the user
identifying information, the social networking system 100 identifies a user
account of the
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user. The communications from the native software application may further
include attribute
information regarding the native software application and/or the client device
102 on which
the native software application is installed. Such attribute information may
indicate, for
example, the operating system of the native software application, the platform
of the native
software application, the version of the native, software application, the
model of the client
device, etc. Based on the identifying information and the attribute
information, the social
networking system 100 determines a client device 102 owned by the user.
[0039] The social networking system 100 may additionally or alternatively
identify a user
as an owner based on communications from a web browsing application installed
on the
client device 102 used by the user to access the website of the social
networking system 100.
Communications received from a web browsing application include user
identifying
information for accessing the social networking system 100. The communications
may
further include attribute information regarding the web browsing application
and/or the client
device 102 on which the web browsing application is installed. Based on the
identifying
information and the attribute information, the social networking system 100
determines a
client device 102 owned by the user.
[0040] In some embodiments, one or more threshold criteria are also
specified for
identifying 310 a user as an owner of a client device 102. In some
implementations, a user is
identified 310 as an owner of a client device 102 if the user has used the
client device 102 at
least a threshold number or percentage of 'times to access the social
networking system using
the user account of the user within a given time period (e.g., within a day,
week, month, year,
etc.). As a specific example, if a user has accessed the social networking
system more than
twenty times using a particular client device 102, the user is identified as
an owner of the
client device 102. As another example, if at least 45% of a user's accesses to
the social
networking system 100 are performed using a particular client device 102, the
user is
identified 310 as an owner of the particular client device 102. Alternatively,
a user is
identified 310 as an owner of a particular client device 102 if the user has
used the client
device 102 to access the social networking system more than any other client
device 102
within a given time period.
[0041] In certain implementations, a user is identified 310 as an owner of
a client device
102 if the client device 102 has been used by the user more than any other
user to access the
social networking system 100. For example, a particular client device 102 may
be an
APPLE IPHONEO. The client device may have been used by a first user 300 times
to
access the social networking system 100 and by a second user 60 times to
access the social
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networking system 100. Because the first user has used the client device 102
more than the
second user to access the social networking system 100 using the client device
102, the social
networking system 100 identifies the first user as an owner of the APPLE
'PHONE . It
will be appreciated that any suitable combination of threshold criteria may be
combined to
identify 310 a user as an owner of a particular type of client device 102.
[0042] In one implementation, one or more social signals from data
maintained by the
social networking system 100 may be used to identify a user as the owner of a
particular type
of client device 102. More specifically, based on analysis of user profile
information
associated with the user, other users connected to the user, the actions of
the user, and/or any
other suitable information of the user maintained by the social networking
system 100, a user
may be identified 310 as an owner of a particular type of client device 102.
For example, a
first user may have been identified 310 as the owner of a particular client
device 102.
Subsequently, a second user not connected to the first user accesses the
social networking
system 100 multiple times using the particular client device 102. Based on
user profiles
associated with the first user and the second user, the social networking
system 100 may
determine that ownership of the client device 102 has changed from the first
user to the
second user.
[0043] Information for the client device 102 owned by a user is stored in
or in association
with the user account and/or user profile of the user. For example, the user
account of the
,
owner in the account store 215 is modified to, include information for the
owned client device
102. Examples of information of a client device stored in the account store
215 include: a
model of the client device 102, a part number of the client device 102, an
operating system of
the client device 102, a manufacturer of the client device 102, a unique
identifier for the client
device 102, a unique identifier for the native application or web browser
installed on the
client device 102, or any other suitable information identifying the client
device 102.
[0044] Exposures of one or more advertisements to the owners of the client
devices 102
are subsequently identified 315. For example, exposures of client device
owners to one or
more advertisements via the owned client device 102, via devices not
identified as being
owned by the owners, via billboards, via periodicals, via television, via the
social networking
system 100, via third party websites 102, or via any suitable channel are
identified 315. For
example, exposures to one or more advertisements via an APPLE 'PHONE 4 are
identified for a user identified as owning the APPLE 'PHONE 4. As another
example,
exposures to an owner of a client device to an advertisement via a third-party
website 103 are
identified 315. ,
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[0045] In one embodiment, exposures to advertisements are identified 315
based on
inferences derived from various social signals and/or other suitable data. For
example, an
owner of a particular client device 102 is identified 315 as having been
exposed to one or
more advertisements based on a current location of the owner included in the
user's user
profile and location information for physical locations associated with the
advertisements
(e.g., a freeway billboard of an advertisement). If the current location of
the client device
owner is within a threshold distance of a physical location associated with an
advertisement,
the client device owner is identified 315 as having been exposed to the
advertisement.
[0046] After identifying the exposures of the one or more advertisements to
the owners,
one or more metrics for the one or more advertisements are generated 320 based
on the
exposures of the client device owners to the one or more advertisements. One
or more of the
metrics may use certain attributes of the client devices 102. For example,
metrics may be
generated for different types of client devices 102 based on model attributes,
product number
attributes, manufacturer attributes, or operating system attributes.
[0047] In one implementation, to generate the metrics, additional data
associated with
owners of the client devices 102 is obtained. In one embodiment, the data is
obtained based
on answers to polls provided to users identified as client device owners 102.
For example, a
poll includes questions asking for impressions about the advertisements to
which a client
device user was exposed or asking for impresions about a brand, product, or
service
associated with the advertisements, or other suitable information.
[0048] The obtained additional data may also or alternatively include
information based
on actions of the identified owners logged by the social networking system
100, which may
include actions internal to or external to the social networking system 100.
The actions may
involve one or more of the presented advertisements, content associated with a
presented
advertisement, an advertiser associated with a presented advertisement, or any
other suitable
information. Examples of actions include: posting user generated content,
liking content,
commenting on content, searching for content, posting statuses, establishing
social
networking connections, posting of reviews, joining of groups, etc.
[0049] The obtained additional data may also or alternatively include
purchase transaction
data. The purchase transaction data may indicate purchases made by the owners
over the
social networking system 100 and/or external to the system 100, where the
purchases are for
products or services associated with the one or more advertisements. For
example, the
purchase transaction data may identify a purchase by a client device owner of
an automobile
promoted by the one or more advertisements. 'In one embodiment, the purchase
transaction
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data is provided subject to user-specified privacy settings from a user
profile, allowing users
to regulate accessibility to purchase transaction data.
[0050] Based on the obtained data associated with client device owners, the
one or more
metrics for the one or more advertisements are generated 320.
[0051] In one embodiment, the generated metrics include exposure or
impression
numbers for the one or more advertisements with respect to the owners of
different types of
client devices 102. Each generated exposure number indicates the number of
times one or
more of the advertisements have been viewed by owners of a type of client
device 102 using
the client device 102. For example, an exposure number indicates the number of
times the
one or more advertisements have been viewed by owners of an APPLE IPHONE@ 5
via an
APPLE WHONE 5. In other embodiments, a generated exposure numbers indicates
the
number of times the one or more advertisements have been viewed by owners of
different
types of client devices 102 regardless of the device used to view the
advertisements (e.g., the
exposure number includes exposures via a client device 102 owned by a user and
via client
devices not identified as being owned by an owner or other sources).
[0052] In another embodiment, the generated metrics include exposure
percentages for
the one or more advertisements with respect to the owners of the different
types of client
devices 102. For example, each generated exposure percentage indicates the
percentage of
the owners of a particular type of client deviccs 102 that was exposed to the
one or more
advertisements over the client device 102. For example, an exposure percentage
specifies
that 30% of the owners of an LG@ ESCAPETM mobile phone were exposed to the one
or
more advertisements via an LG@ ESCAPETM mobile phone. Another exposure
percentage
may indicate that 75% of owners of client devices 102 running the APPLE i0S
operating
system were exposed to the one or more advertisements over client devices 102
running the
APPLE i0S operating system. In other embodiments, the generated exposure
percentages
identify the percentage of owners of the client devices 102 that were exposed
to the one or
more advertisements regardless of the source of the exposure.
[0053] In one embodiment, the generated metrics may describe conversion
events (e.g.,
purchases, accessing of advertisements, accessing of landing pages associated
with an
advertisement) with respect to owners of different types of client devices
102. In the
embodiment, such conversion metrics measure the effectiveness of the one or
more
advertisements in facilitating the owners of the different types of client
devices 102 to
perform some action. For example, the metrics may measure the impact of the
advertisements in causing owners to purchaseproducts associated with the
advertisements,
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perform certain actions (e.g., commenting on, liking, sharing, searching for)
on content
associated with the advertisements, etc.
[0054] In the embodiment, such metrics are generated using various holdout
and sample
groups including owners of the client devices 102. For example, owners of
various types of
client devices 102 are randomly or pseudo-randomly assigned to holdout or
sample groups.
Each of the holdout and sample groups may include users with identical or
similar
demographic characteristics to facilitate comparisons between the groups.
Owners assigned
to a sample group are presented with the one or more of the advertisements
while owners in a
holdout group are not presented with the advertisements.
[0055] Based on differences in the previously obtained data (e.g., polling
data, purchase
transaction data, observed actions, etc.) between owners of types of client
devices in the
holdout group and owners of corresponding types of client devices in the
sample group,
metrics indicating the impact of the advertisements on the owners of the
different types of
client devices 102 are generated 320. For example, an advertisement promotes a
particular
brand of shoes, so a metric indicating the impact of the advertisement on
purchases of the
brand of shoes by owners of the APPLE IPHONE ,05 is generated 320. The metric
may
indicate a rate at which APPLE IPHONE 5 owners purchase the shoes after
being
presented with the advertisement. A similar metric may also be generated for
owners of the
NOKIA LUMIA . Such metrics may be based on the obtained purchase data for the
owners. Additional details regarding the generation of metrics using holdout
groups may be
found in U.S. Patent Application No. 13/658,480, filed on October 23, 2012,
titled
"Determining Advertising Effectiveness Based on Observed Actions in a Social
Networking
System," which is hereby incorporated by reference in its entirety. Any other
suitable metrics
for the one or more advertisements may be generated 320 based on the
identified client device
ownership. The generated metrics are provided 325 to an advertiser or any
other suitable
entity.
[0056] In one embodiment, the metrics may describe market share or
ownership shifts
related to various client devices. In generating such metrics, client devices
previously owned
by various users are identified. The client devices currently owned by the
same users are also
identified. Based on the identified information, differences between those
client devices
previously owned by the users and those client devices currently owned by the
users are
analyzed. For example, a difference between the number/percentage of users
previously
owning a particular type of client device and the number/percentage of users
currently owning
the particular type of client device can be scorriputed as part of the
analysis. Based on the
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CA 2967671 2017-05-19
analysis, metrics describing market shifts or changes related to ownership of
the client
devices are generated.
[0057] As a specific example, the social networking system may identify
users that
previously owned the APPLE IPHONE@ 3, The social networking system may
further
identify the client devices now owned by the users, such as the APPLE IPHONE@
4S and
APPLE IPHONE@ 5. Based on such information, the social networking system can
provide metrics indicating the manner in which ownership or market share of
the APPLE
[PHONE 3 has changed or shifted to other types of client devices.
[0058] As another specific example, the social networking system may
identify users that
previously owned ANDROID based client devices associated with a particular
service
provider. The social networking system may additionally identify those client
devices
currently owned by the same users, and the service providers associated with
the currently
owned client devices. Based on such information, the social networking system
may generate
metrics describing the manner in which the market share of the service
provider has shifted
over time with respect to owners of ANDROID based client devices.
Process for Generating Metrics Measuring Advertising Impact on Client Device
Ownership
[0059] FIG. 4 illustrates one embodiment of a process 400 for generating
advertising
metrics measuring advertising impact based on client device ownership. Other
embodiments
can perform the steps of the process 400 in different orders and can include
different,
additional, and/or fewer steps.
[0060] In the process, social networking system users are randomly or
pseudo-randomly
assigned 410 to a sample group or holdout group for one or more
advertisements. Each of the
holdout and sample groups may include users with identical or similar
demographic
characteristics. In one aspect, each of the one or more advertisements may be
associated with
a particular type of client device 102, such as a particular mobile phone
model. For example,
the one or more advertisements may promote a particular type of client device
102.
[0061] After the client device owners are assigned 410 to the holdout group
or to the
sample group, the one or more advertisements are presented to the users in the
sample group
and withheld from being presented to users in the holdout group. More
specifically, when an
advertisement from the one or more advertisements is selected for presentation
to a user, the
social networking system 100 determines whether the user is assigned to the
holdout group or
the sample group. If the user is assigned to the holdout group, the user is
not presented with
the advertisement. If the user is assigned to the sample group, the user is
presented with the
advertisement.
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[0062] After presentation of the one or more advertisements, one or more
owners of client
devices 102 of the particular type associated with the one or more
advertisements are
identified 415 via the social networking system 100. For example, for
advertisements
promoting the APPLE 'PHONE 5 model, -users of the social networking system
100
indicated as owning an APPLE IPHONE 5 are identified 415. Client device
owners may
be identified 415 as described above in conjunction with the process described
in FIG. 3. For
example, owners of client devices 102 may be identified based on accesses to
the social
networking system 100 by native software applications and/or web browsing
applications
installed on client devices 102.
[0063] Thereafter, client device owners included in the sample group and
client device
owners included in the holdout group are identified 418 from the identified
owners of the
client devices 102 associated with the one or more advertisements. Based on
the identified
owners for the holdout and sample groups, conversion metrics indicating the
effectiveness of
the advertisements in facilitating ownership of the type of client device 102
are generated
420.
[0064] To generate the metrics, in one embodiment, the number or percentage
of users in
the holdout group identified as owning units of the client device 102 of the
type is identified.
The number or percentage of users in the sample group identified as owning
units of the
,
client device 102 of the type is also identified. Thereafter, differences in
the number or
percentage of users owning a unit of the client device 102 in the sample group
is compared to
the number or percentage of users owning a unit of the client device 102 in
the holdout group.
Based on the comparison, one or more metrics providing a measure of the effect
of the
advertisements on client device ownership are generated 420. For example, it
may be
determined that 10% of the users in the sample group own an APPLE IPHONE 5
after the
advertisements were presented, while 5% of the users in the holdout group own
an APPLE
IPHONE 5 after the advertisements were presented. Hence, a generated metric
may
indicate that the advertisements increased ownership of the APPLE IPHONE 5
by five
percentage points.
[0065] To generate the metrics, in another embodiment, the number or
percentage of
users in the holdout group identified as owning a client device 102 of the
type prior to
presentation of advertisements is determined. The number or percentage of
users in the
holdout group identified as owning a client device 102 of the type after
presentation of the
advertisements is also determined. Thereafter,, the number or percentage
related to ownership
prior to presentation of the advertisements and the number or percentage
related to ownership
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after presentation of the advertisements are compared. For example, a
difference value can be
determined between the two numbers or two percentages of the holdout group.
[0066] In addition, the number or percentage of users in the sample group
identified as
owning a client device 102 of the type priOr to' presentation of
advertisements is determined.
The number or percentage of users in the sample group identified as owning a
client device
102 of the type after presentation of the advertisements is also determined.
Thereafter, the
number or percentage related to ownership prior to presentation of the
advertisements and the
number or percentage related to ownership after presentation of the
advertisements are
compared. For example, a difference value can be determined between the two
numbers or
two percentages of the sample group. Thereafter, the metrics may be generated
by comparing
and contrasting the difference value for the holdout group and the difference
value for the
sample group.
[0067] Additional details regarding the use of holdout groups in generating
advertising
metrics may be found in U.S. Patent Application No. 13/658,480, filed on
October 23, 2012,
titled "Determining Advertising Effectiveness Based on Observed Actions in a
Social
Networking System," which is hereby incorporated by reference in its entirety.
The generated
metrics are provided 425 to an advertiser or another suitable entity.
[0068] In one embodiment, rather than identifying specific client devices
(i.e., specific
. ,
instances or units of client devices) owned by users, the social networking
system 100
identifies types of client devices owned by users. In such instances, a
specific instance of a
client device 102 is not associated with a particular user. Rather, a type
(e.g., a model) of the
client device 102 is associated with the particular user.
[0069] In one embodiment, in addition to identifying client device
ownership, the social
networking system 100 identifies service providers utilized by and/or
otherwise associated
with the client devices owned by users. In such instances, the metrics
generated by the social
networking system 100 may additionally include service provider type as a
dimension. For
example, the metrics generated by the social networking system 100 may
describe the number
or percentage of users identified as being customers of AT&T based on the
users'
ownership of client devices associated with AT&T .
[0070] In yet another embodiment, the social networking system 100
associates or merges
various types of information available over the social networking system with
client device
ownership information. For example, the social networking system 100 may
associate user
profile information (e.g., user identities, user interests, education
information, demographic
information, etc.), user action information (user approval actions, user
commenting actions,
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CA 2967671 2017-05-19
etc.), user social network connection information (e.g., user friendship
information), and/or
any other information of a social networking system with identified client
device owners.
Based on such information, the social networling system 100 may identify
various
relationships or links between client device ownership and social networking
system
information. As a specific example, the social networking system 100 may
associate user
profile information with client device ownership information to identify
owners of a
particular type of client device that are also interested in sports as stated
in the owners' social
networking system user profiles. As another example, the social networking
system 100 may
associate user action information to identify customers of particular client
device service
providers that have provided approval for (e.g., "liked") certain
advertisements presented over
the social networking system 100.
Summary
[0071] The foregoing description of the embodiments of the invention has
been presented
for the purpose of illustration; it is not intended to be exhaustive or to
limit the invention to
the precise forms disclosed. Persons skilled in the relevant art can
appreciate that many
modifications and variations are possible in light of the above disclosure.
[0072] Some portions of this description describe the embodiments of the
invention in
terms of algorithms and symbolic representations of operations on information.
These
algorithmic descriptions and representations are commonly used by those
skilled in the data
processing arts to convey the substance of their work effectively to others
skilled in the art.
These operations, while described functionally, computationally, or logically,
are understood
to be implemented by computer programs or equivalent electrical circuits,
microcode, or the
like. Furthermore, it has also proven convenient at times, to refer to these
arrangements of
operations as modules, without loss of generality. The described operations
and their
associated modules may be embodied in software, firmware, hardware, or any
combinations
thereof.
[0073] Any of the steps, operations, or processes described herein may be
performed or
implemented with one or more hardware or software modules, alone or in
combination with
other devices. In one embodiment, a software module is implemented with a
computer
program product comprising a computer-readable medium containing computer
program
code, which can be executed by a computer processor for performing any or all
of the steps,
operations, or processes described.
[0074] Embodiments of the invention may also relate to an apparatus for
performing the
operations herein. This apparatus may be specially constructed for the
required purposes,
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and/or it may include a general-purpose computing device selectively activated
or
reconfigured by a computer program stored in the computer. Such a computer
program may
be stored in a tangible computer readable stor.uge medium or any type of media
suitable for
storing electronic instructions, and coupled to a computer system bus.
Furthermore, any
computing systems referred to in the specification may include a single
processor or may be
architectures employing multiple processor designs for increased computing
capability.
[0075] Embodiments of the invention may also relate to a computer data
signal embodied
in a carrier wave, where the computer data signal includes any embodiment of a
computer
program product or other data combination described herein. The computer data
signal is a
product that is presented in a tangible medium or carrier wave and modulated
or otherwise
encoded in the carrier wave, which is tangible, and transmitted according to
any suitable
transmission method.
[0076] Finally, the language used in the specification has been principally
selected for
readability and instructional purposes, and it may not have been selected to
delineate or
circumscribe the inventive subject matter. It is therefore intended that the
scope of the
invention be limited not by this detailed description, but rather by any
claims that issue on an
application based hereon. Accordingly, the disclosure of the embodiments of
the invention is
intended to be illustrative, but not limiting, oPthe scope of the invention,
which is set forth in
the following claims.
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